In a second empirical blackanalysis, we aggregate the stock market indices to form a financial portfolio with a predetermined level of risk, and estimate its optimal allocation weights by implementing our new optimization procedure. We then compute the out-of-sample portfolio's VaR and ES and evaluate the predictions using the univariate backtesting procedures of [1]}, [2]} and [3]}.
blackThe empirical analysis reveals that our multivariate method produces the lowest average losses compared to other existing strategies based on the multivariate Normal and t- distributions, regardless of the scoring function being used. In addition, we find that the proposed methodology overall yields the highest Sharpe Ratio and the least concentrated portfolio allocations.
